The development of markerless motion capture systems is motivated by the need to address contemporary needs to understand normal and pathological human movement without the encumbrance of markers or fixtures placed on the subject, while achieving the quantitative accuracy of marker based systems. To date, markerless methods are not widely available because the accurate capture of human movement without markers is technically challenging. Biomechanical, medical, sports and animation applications of markerless capture have been limited by the lack of both accuracy and robustness of such methods.
Previous work has demonstrated that minor changes in patterns of locomotion can have a profound impact on the outcome of treatment or progression of musculoskeletal pathology. Therefore the ability to address emerging clinical questions on problems that influence normal patterns of locomotion requires new methods that would limit the risk of producing artifact due to markers or the constraints of the testing methods. For example, the constraints of the laboratory environment as well as the markers placed on the subjects can mask subtle but important changes to the patterns of locomotion. It has been shown that the mechanics of walking was changed in patients with anterior cruciate ligament deficiency of the knee; functional loading influenced the outcome of high tibial osteotomy; functional performance of patients with total knee replacement was influenced by the design of the implant, and the mechanics of walking influenced the disease severity of osteoarthritis of the knee.
Each of these clinical examples is associated with subtle though important changes to the mechanics of walking, which indicates several necessary requirements for the next significant advancement in the understanding of normal and pathological human movement. The present invention addresses these needs and advances the art of markerless motion capture and the applications thereof. In addition, the advancements introduced by the present invention will also facilitate applications in other fields such as: i) sports by allowing for example the assessment of athletes' motion/performances in their natural environment, ii) entertainment, gaming and animation by utilizing for example markerless motion captured data for rendering engines and/or for navigation in user interfaces, or iii) surveillance by allowing for example the identification of a unique motion-signature for individuals.